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The study makes use of polynomial chaos expansions to compute Sobol' indiceswithin the frame of a global sensitivity analysis of hydro-dispersiveparameters in a simplified vertical cross-section of a segment of thesubsurface of the Paris Basin. Applying conservative ranges, the uncertainty in78 input variables is propagated upon the mean lifetime expectancy of watermolecules departing from a specific location within a highly confining layersituated in the middle of the model domain. Lifetime expectancy is ahydrogeological performance measure pertinent to safety analysis with respectto subsurface contaminants, such as radionuclides. The sensitivity analysisindicates that the variability in the mean lifetime expectancy can besufficiently explained by the uncertainty in the petrofacies, \ie the sets ofporosity and hydraulic conductivity, of only a few layers of the model. Theobtained results provide guidance regarding the uncertainty modeling in futureinvestigations employing detailed numerical models of the subsurface of theParis Basin. Moreover, the study demonstrates the high efficiency of sparsepolynomial chaos expansions in computing Sobol' indices for high-dimensionalmodels.

reliability engineering and system safety

Using sparse polynomial chaos expansions for the global sensitivity  analysis of groundwater lifetime expectancy in a multi-layered  hydrogeological model